Transformers: how does the decoder final layer output the desired token?
I found the answer by reading the paper referenced by that section, Using the output embedding to improve language models

Based on this observation, we propose threeway weight tying (TWWT), where the input embedding of the decoder, the output embedding of
the decoder and the input embedding of the encoder are all tied. The single source/target vocabulary of this model is the union of both the source
and target vocabularies. In this model, both in the
encoder and decoder, all subwords are embedded
in the same duo-lingual space.

It seems like they learned a single embedding matrix ($n^e + n^f$) x $d^{model}$ in dimension.